Original presentation date: 19 Dec 2024
2025-04-13
Goal of project
Analysis plan and progress
Some selected results
Next steps and timeline
The goal is to determine to what degree the Core data can be used to approximate the HRS/HCAP classification.
The procedure will be to classify 2016 HRS/HCAP participants into cognitive impairment categories (normal, mild cognitive impairment, dementia) using only data from the HRS 2016 Core interview (i.e., omitting all HRS/HCAP data).
This is only one of several possible approaches to cognitive classification of Core participants.
| Statistical analysis plan | GDoc |
| Detailed analysis results | HTML |
| Mplus output final factor model | TXT |
1. Factor model for general cognition in HRS/Core (in R)
2. Adjustment, standardization and normalization (in R)
3. Equivalent cut point for identifying severe and moderate cognitive impairment to that used in HRS/HCAP algorithm
4. Operationalize functional impairment in HRS/Core
5. Run and compare algorithms
6. Reporting
| Fit statistic | Value |
|---|---|
| RMSEA : Estimate | 0.057 |
| CFI | 0.961 |
| SRMR | 0.041 |
| Item | Label | Std Factor Loading |
|---|---|---|
| vdori | Orientation to time | 0.485 |
| vdlfl1z | Animal naming | 0.591 |
| vdlfl2 | Scissors & cactus | 0.678 |
| vdlfl3 | President & vice-president | 0.599 |
| vdwddelz | Delayed word recall | 0.589 |
| vdexf7z | Number series | 0.642 |
| vdsevens | Serial sevens | 0.706 |
| vdcount | Count backwards from 20 | 0.567 |
Note: items with a “z” at the end are continuous indicators, the others are categorical indicators.
The single factor model fits well by conventional fit criteria.
Like the HRS/HCAP factor models, we do not include immediate memory performance in the model.
We do include naming and serial 7s, which are not in HRS/HCAP models
During the meeting we discussed that the model may be too heavy in “other” (notably serial 7s, number series) and less “memory” and this may be problematic for AD. We will explore other solutions.
In the normative
reference group
NOT in the normative
reference group
In the normative
reference group
NOT in the normative
reference group
NOT in HRS/HCAP
| Characteristic | N = 2,9931 |
|---|---|
| Number of domains impaired | |
| No domains | 1,935 (65%) |
| 1 domain | 587 (20%) |
| 2+ domains | 471 (16%) |
| 1 n (%) | |
Number of domains impaired, based
on full HRS/HCAP algorithm using 5
individual domains
Centiles of adjusted, normalized, standardized factor score in HRS/Core
|
Level of cognitive impairment (HRS)
|
Total | ||||
|---|---|---|---|---|---|
| None | Mild | Severe | Unknown | ||
| Number of domains impaired | |||||
| No domains | 1,528 | 307 | 88 | 12 | 1,935 |
| 1 domain | 312 | 164 | 99 | 12 | 587 |
| 2+ domains | 101 | 101 | 218 | 51 | 471 |
| Total | 1,941 | 572 | 405 | 75 | 2,993 |
Number of domains impaired,
based on full HRS/HCAP
algorithm using 5 individual
domains
Based on matching centiles of adjusted,
normalized, standardized factor score in
HRS/Core
1. Factor model for general cognition in HRS/Core (in R)
2. Adjustment, standardization and normalization (in R)
3. Equivalent cut point for identifying severe and moderate cognitive impairment to that used in HRS/HCAP algorithm
4. Operationalize functional impairment in HRS/Core
5. Run and compare algorithms
6. Reporting